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Variability in Acti...
Variability in Action Selection Relates to Striatal Dopamine 2/3 Receptor Availability in Humans : A PET Neuroimaging Study Using Reinforcement Learning and Active Inference Models
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Adams, Rick A. (author)
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- Moutoussis, Michael (author)
- Karolinska Institutet
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Nour, Matthew M. (author)
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Dahoun, Tarik (author)
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Lewis, Declan (author)
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Illingworth, Benjamin (author)
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Veronese, Mattia (author)
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Mathys, Christoph (author)
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de Boer, Lieke (author)
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- Guitart-Masip, Marc (author)
- Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI),Max Planck-UCL Centre for Computational Psychiatry and Ageing Research, UK
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Friston, Karl J. (author)
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Howes, Oliver D. (author)
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Roiser, Jonathan P. (author)
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(creator_code:org_t)
- 2020-02-21
- 2020
- English.
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In: Cerebral Cortex. - : Oxford University Press (OUP). - 1047-3211 .- 1460-2199. ; 30:6, s. 3573-3589
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https://doi.org/10.1...
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Abstract
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- Choosing actions that result in advantageous outcomes is a fundamental function of nervous systems. All computational decision-making models contain a mechanism that controls the variability of (or confidence in) action selection, but its neural implementation is unclear-especially in humans. We investigated this mechanism using two influential decision-making frameworks: active inference (AI) and reinforcement learning (RL). In AI, the precision (inverse variance) of beliefs about policies controls action selection variability-similar to decision 'noise' parameters in RL-and is thought to be encoded by striatal dopamine signaling. We tested this hypothesis by administering a 'go/no-go' task to 75 healthy participants, and measuring striatal dopamine 2/3 receptor (D2/3R) availability in a subset (n = 25) using [C-11]-(+)-PHNO positron emission tomography. In behavioral model comparison, RL performed best across the whole group but AI performed best in participants performing above chance levels. Limbic striatal D2/3R availability had linear relationships with AI policy precision (P = 0.029) as well as with RL irreducible decision 'noise' (P = 0.020), and this relationship with D2/3R availability was confirmed with a 'decision stochasticity' factor that aggregated across both models (P = 0.0006). These findings are consistent with occupancy of inhibitory striatal D(2/3)Rs decreasing the variability of action selection in humans.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Neurosciences (hsv//eng)
Keyword
- active inference
- action selection
- decision temperature
- dopamine 2/3 receptors
- go no-go task
- reinforcement learning
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Adams, Rick A.
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Moutoussis, Mich ...
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Nour, Matthew M.
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Dahoun, Tarik
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Lewis, Declan
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Illingworth, Ben ...
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show more...
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Veronese, Mattia
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Mathys, Christop ...
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de Boer, Lieke
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Guitart-Masip, M ...
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Friston, Karl J.
-
Howes, Oliver D.
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Roiser, Jonathan ...
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show less...
- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Basic Medicine
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and Neurosciences
- Articles in the publication
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Cerebral Cortex
- By the university
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Stockholm University
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Karolinska Institutet